Topic: [ENDED][SHP] Sharpe Capital - Sentiment & Financial Protocol. - page 81. (Read 47835 times)

This is the minimum during pre-sale. During the main crowd-sale the minimum will be $100 USD.

If you're interested in the pre-sale, you can sign up here: https://sharpe.capital/tokens#pre-sale

Thanks!

Minimum participation $10k I got it right, it is a minimum sum of taking part in ico

I must say that you whole presentation really looks convincing and I am pretty certain that you are completely right and people will go wild about this ICO. That counts at least for me

Thank you, that looks really good. I look forward to the launch 

Oh great.I like it when the supply is low because that yields more returns in the short to long term forinvestors.Anything upto 50million tokens will bevery cool

https://medium.com/@sharpecapital/sharpe-capital-pre-sale-bb53578d2ef4

Pre-sale registration form now available on the Sharpe Capital website. People who have shown interest via email will be contacted in order to whitelist their contributions.

For more information check out this new blog post:

https://medium.com/@sharpecapital/sharpe-capital-pre-sale-bb53578d2ef4

Hey - thanks for the compliment!

Crowdsale will be on November 6 at 14:00 GMT. Pre-sale will commence on October 9 at 14:00 BST (GMT+1) and run for 28 days.

The pre-sale discounts are included below:

$10K-$50k —> 10%
$50k-$250k —> 20%
$250k-$1M —> 30%

Great project, when is the ico date?

Any presale discount?

Good old Mr. Sharpe finally gets proper recognition in the blockchain space!

The total supply will depend on the amount raised at the end of the sale (1 ETH = 2000 SHP).

Lewis answered this in telegram before


There is no 'minimum cap'. The level of demand we have received from pre-sale registrations already exceeds our projections and expectations, there is no concern regarding not achieving a sufficient level of participation in the SHP sale to deliver the platform/protocol according to the schedule outlined in our roadmap. In addition to SHP participation from the community, we are looking to onboard VC investment post-TGE, and have received enquiries to this end.

you realy have amazing target, i'll join your social media campaign because you have already make great algoritm and i support this
involving AI will reduce mistake by human and help better movement, will try join pre-sale
btw where i can find how much token you created? what happen if not all token sold?
sorry, can't find it on the website

Look at your official website, in the block chain area， there are dragons and fishes jumbled together, one really wants to do something the team, because you always take the technology as the core, and has been applied in our daily life.

Thank you Lewis,

I like that you will be joining the Bancor universe as I'm also a Bancor investor and supporter 

Is there a minimum amount you need to raise to go forward with your venture?

I look forward to this sale, all the best!

Hi MrAtom!

We're implementing a $10m USD hard-cap for the pre-sale, with the crowdsale hard-cap being undisclosed. The reason for this is that we're implementing "dynamic ceilings" during the live-sale, as pioneered by Status, to ensure an even distribution of SHP ownership and to make sure our governance and voting mechanism is not compromised by a concentration of SHP tokens in a few hands.

Therefore, we're advising larger contributors to join in the pre-sale, of which the first hour will be uncapped. We can tell you that the hard-cap of the crowdsale, and therefore maximum market-cap, will be between $60m and 90m USD.

We have committed to using anything raised above $45m USD for token liquidity. SHP tokens will be backed by the Bancor protocol, and we will calculate the exact reserve once we know how much we've raised. If there are excess funds above $45m USD and the Bancor reserve, we will reserve these to be used for additional liquidity in the future, as required.

Thanks,

Lewis

What is the cap for this sale?

Patterns observed in 'technical analysis' are generally unreliable due to a large degree of stochasticity. There is no evidence to suggest that technicalism out-performs the market, on average. There are undeniably historical patterns to some extent, despite the well-known observation that future performance cannot be predicted by historical prices. These patterns emerge as a result of the collective cognitive behavioural processes of traders. We go beyond looking at simple positive and negative sentiment, by not only crowd-sourcing actual opinions from those with a proof-of-stake (instead of merely attempting to infer using Natural Language Processing), and we are combining this analysis of social and 'old' media to infer predicted 'investor responses' to the media they consume.

To quote the white paper: "Investor sentiment, whether rational or irrational, causes an asset’s market trading value to deviate from its ’intrinsic’ value as determined by fundamentalist microeconomic indicators. That is, trading is fundamentally driven by human decision-making based on individual traders’ beliefs, perception and confidence levels." - It is this process responsible for technicalism, and therefore we incorporate these processes at a far more fundamental level.

Quantitative modelling alone only produces mediocre predictive capabilities, because markets are fundamentally driven by two factors:

1) the tendency of an asset to return to its "intrinsic" value
2) irrational investor sentiment, driving an asset away from its intrinsic value

We have married these two approaches together to create a unique investment algorithm that is capable of consistently beating the market, and incentivises our token holders to provide the high-quality sentiment that we need to satisfy point 2 above. By paying rewards to holders of our tokens (SHP), linked to proof-of-stake, proof-of-work and proof-of-reputation, we ensure we capture the highest quality sentiment possible, and fairly reward those that help our fund generate better returns, with bi-annual Ether payments.

I would encourage you to read section 6 of the white paper, which describes the dynamics of crowdsourcing sentiment in great detail. The ultimate premise can be broken down into two points:

1) when there is something at stake, people will work harder to improve the sentiment they provide
2) when this information is provided by "the crowd", the quality & accuracy will far exceed that of any individual

Perhaps the most novel element of our crowdsourced sentiment analysis is the fact that, unlike prediction markets, there are no odds and you can never lose the SHP you have staked. Because the "reputation score" is calculated on a rolling basis, bad sentiment only serves to reduce any future rewards that sentiment providers may earn. Of course a low reputation score can be improved by providing more good sentiment in the future.

We appreciate our concepts aren't the easiest to grasp, but I heard a wise man once said: the hardest things to understand are usually the best

Users provide their sentiment with respect to certain stocks (bullish/bearish) and they get rewarded in function of the accuracy of their predictions and the amount of SHP tokens held. There will be a reputation score system that will constantly update itself as the user provides sentiment feedback.

For a more in-depth explanation and an example refer to page 34 of the White Paper:



In equation 1, Rcurrent is the users current reputation score, calculated weekly based on how accurate the provided sentiment was. R is linearly modulated by a scalar constant, m (equation 2) positively for each correct prediction and negatively for each incorrect prediction. That is, for each correct prediction the reputation score is increased or decreased by multiplying the user’s previous reputation score, Rprevious, by m, and adding
this to Rcurrent. This is repeated for incorrect predictions, but by reducing R by R · m instead of increasing it. The maximum value of R is 1, and the minimum value is 0, as stated in equation 3.

The impact of predictions on a user’s reputation score is perhaps best demonstrated by example (let us assume that m = 0.05):

• A user has R = 0.5, and provides 6 correct and 3 incorrect predictions.
Their new R is (0.5 + (6 ∗ 0.5 ∗ 0.05)) − (3 ∗ 0.5 ∗ 0.05) = 0.575. This represents an increase of 7.5 percentage points for all rewards received by this user for correct predictions.
• A user has R = 0.2, and provides 6 correct and 3 incorrect predictions.
Their new R is (0.2 + (6 ∗ 0.2 ∗ 0.05)) − (3 ∗ 0.2 ∗ 0.05) = 0.23. This represents an increase of 3 percentage points for all rewards received by this user for correct predictions.
• A user has R = 0.5, and provides 3 correct and 6 incorrect predictions.
Their new R is (0.5 + (3 ∗ 0.5 ∗ 0.05)) − (6 ∗ 0.5 ∗ 0.05) = 0.425. This represents a decrease of 7.5 percentage points for all rewards received by this user for correct predictions.
• A user has R = 0.2, and provides 3 correct and 6 incorrect predictions.
Their new R is (0.2 + (6 ∗ 0.2 ∗ 0.05)) − (3 ∗ 0.2 ∗ 0.05) = 0.17. This represents a decrease of 3 percentage points for all rewards received by this user for correct predictions.

As the example above illustrates, changes in a user’s R are linear - that is, the relative change in R is dependent only on the accuracy of the user’s provided sentiment, and not the previous value of R.